Wei Ling Chen

Transplantation of autologous endothelial progenitor cells in porous PLGA scaffolds create a microenvironment for the regeneration of hyaline cartilage in rabbits

OBJECTIVE Repairing articular cartilage is clinically challenging. We investigated a simple, effective and clinically feasible cell-based therapeutic approach using a poly(lactide-co-glycolide) (PLGA) scaffold seeded with autologous endothelial progenitor cells (EPC) to repair a full-thickness osteochondral defect in rabbits using a one-step surgery. METHODS EPC obtained by purifying a small amount of peripheral blood from rabbits were seeded into a highly porous, biocompatible PLGA scaffold, namely, EPC-PLGA, and implanted into the osteochondral defect in the medial femoral condyle. Twenty two rabbits were randomized into one of three groups: the empty defect group (ED), the PLGA-only group or the EPC-PLGA group. The defect sites were evaluated 4 and 12 weeks after implantation. RESULTS At the end of testing, only the EPC-PLGA group showed the development of new cartilage tissue with a smooth, transparent and integrated articular surface. Moreover, histological analysis showed obvious differences in cartilage regeneration. At week 4, the EPC-PLGA group showed considerably higher TGF-β2 and TGF-β3 expression, a greater amount of synthesized glycosaminoglycan (GAG) content, and a higher degree of osteochondral angiogenesis in repaired tissues. At week 12, the EPC-PLGA group showed enhanced hyaline cartilage regeneration with a normal columnar chondrocyte arrangement, higher SOX9 expression, and greater GAG and collagen type II (COLII) content. Moreover, the EPC-PLGA group showed organized osteochondral integration, the formation of vessel-rich tubercular bone and significantly higher bone volume per tissue volume and trabecular thickness (Tb.Th). CONCLUSION The present EPC-PLGA cell delivery system generates a suitable in situ microenvironment for osteochondral regeneration without the supplement of exogenous growth factors.

A Rule-Based Decision-Making Diagnosis System to Evaluate Arteriovenous Shunt Stenosis for Hemodialysis Treatment of Patients Using Fuzzy Petri Nets

This paper proposes a rule-based decision-making diagnosis system to evaluate arteriovenous shunt (AVS) stenosis for long-term hemodialysis treatment of patients using fuzzy petri nets (FPNs). AVS stenoses are often associated with blood sounds, resulting from turbulent flow over the narrowed blood vessel. Phonoangiography provides a noninvasive technique to monitor the sounds of the AVS. Since the power spectra changes in frequency and amplitude with the degree of AVS stenosis, it is difficult to make a human-made decision to judge the degree using a combination of those variances. The Burg autoregressive (AR) method is used to estimate the frequency spectra of a phonoangiographic signal and identify the characteristic frequencies. A rule-based decision-making method, FPNs, is designed as a decision-making system to evaluate the degree of stenosis (DOS) in routine examinations. For 42 long-term follow-up patients, the examination results show the proposed diagnosis system has greater efficiency in evaluating AVS stenosis.

Residual Stenosis Estimation of Arteriovenous Grafts Using a Dual-Channel Phonoangiography With Fractional-Order Features

The residual stenosis estimation of an arteriovenous shunt is a valuable for evaluating outcomes of percutaneous transluminal angioplasty (PTA) treatment and surgical revision. This paper proposes a dual-channel phonoangiography (PCG) with fractional-order features to estimate the residual of stenosis estimation of arteriovenous shunt. The auscultation technique provides a noninvasive tool to monitor the degrees of arteriovenous grafts (AVGs). Then, support methods, such as the Burg autoregressive (AR) method and self-synchronization error formulation (SSEF), are used to extract fractional-order features between the loop site (L-site) and venous anastomosis site (V-site). Using 2-D patterns (nonlinear mapping), a generalized regression neural network (GRNN) is designed as a nonlinear estimate model to indicate the outcome of surgical revision or AVG stenosis upon routine monthly examinations. For 42 long-term follow-up patients, the results of examination show the proposed GRNN-based screening model efficiently estimates residual stenosis.

Handmade Trileaflet Valve Design and Validation for Pulmonary Valved Conduit Reconstruction Using Taguchi Method and Cascade Correlation Machine Learning Model

Pulmonary valve diseases in children and adults include different degrees of stenosis, regurgitation, or congenital defects. Valve repair or replacement surgery is used to treat valvular dysfunction and to improve regurgitations flow for pulmonary valve pathologies. Handmade trileaflet valve designs with different ranges of diameters have been used for pulmonary valved conduit reconstruction among children or adult patients with available conditions. In this paper, we propose a multiple regression model as a cascade-correlation-network-based estimator to determine optimal trileaflet parameters, including width, length, and upper/lower curved structures, for trileaflet valve reconstruction. The diameter of the main pulmonary artery is determined via computed tomography pulmonary angiography, and a trileaflet valve template is rapidly sketched. The actual valve is constructed using an expanded polytetrafluoroethylene material. Using an experimental pulmonary circulation loop system, design parameters and valve efficacy can be validated by the Taguchi method through calculation of signal-to-noise ratios. Experimental results indicate that in contrast to commercial valve stents, the handmade trileaflet valve exhibits good performance and is a valuable option in treatment of severe pulmonary regurgitation.

An equivalent astable multivibrator model to assess flow instability and dysfunction risk in in-vitro stenotic arteriovenous grafts

Narrowed vessel accesses produce blood flow changes, and induce flow instability and vessel wall vibration, resulting in blood pressure, flow velocity, and flow resistance increases. The vessel wall vibrates and propagates the low axial blood flow, as representing the resistance (R) to blood flow. The compliance is a blood pressure-blood volume relation, representing the systole and diastole capacity of the blood vessel. These dynamic behaviors increase blood flow resistances and reduce blood vessel compliances. Vibration phenomena result on the elastic vessel walls and induce simple harmonic motion due to transverse vibration pressure (TVP). The rise time, amplitude, and pulse duration of transverse waves are determined by the flow resistances (R) and vessel compliances (C). Thus, a stenotic arteriovenous access has high resistance and low compliance, which can be expressed an astable multivibrator as an equivalent model consisting of a lumped resistor (R) and a lumped capacitor (C). TVPs oscillation frequency, rise time, and amplitude are determined by the flow resistances and vessel compliances. Hence, an astable multivibrator is used to model TVP parameters to estimate negative time constants, τ=(R× C), which are used to evaluate the flow instability and the dysfunction risk in in-vitro arteriovenous grafts (AVGs). Experimental results show the average negative time constants have the positive correlation as the degree of stenosis (DOS) increases (R2 = 0.8944), and their variations with the flow resistance and vessel compliance are also validated. Positive pole values, s=(-1/τ), are used to show that the force responses of the vessel walls grow in a finite time, 0.5415 ± 7.60 × 10-3 sec, and the equivalent model would be also unstable as DOS increases (R2 = 0.8802). By comparison with hemodynamic analysis, the finding of proposed model can be further carried out for screening AVG dysfunction risk during hemodialysis treatment.

Estimating Residual Stenosis for an Arteriovenous Shunt Using a Flexible Fuzzy Classifier

This article determines whether the diameter of a vascular lumen is clinically valuable for hemodialysis therapy. A novel method is proposed that uses a flexible fuzzy classifier (FFC) implementing a curve approximation function to estimate residual stenosis in an arteriovenous shunt (AVS). The auscultation method provides a noninvasive technique for monitoring the degree of AVS stenoses. The Burg autoregressive method is used to identify the characteristic spectra for changes in frequency and amplitude between frequencies of 25 and 800 Hz. Fractional order self-synchronization error formulation is then used to quantify the degree of stenosis between normal access and AVS stenosis in the frequency spectra. To estimate the diameter of a vascular lumen, the FFC is used to create a nonlinear prediction model. For the 42 long-term patients studied, the results of this examination show that the proposed prediction model estimates residual stenosis efficiently.

Customized Handmade Pulmonary Valved Conduit Reconstruction for Children and Adult Patients Using Meta-Learning Based Intelligent Model

Percutaneous pulmonary valve implantation is an improved technique that is used to treat narrowed pulmonary valves or leaky pulmonary valves in patients with congenital heart disease. This technique represents a promising strategy to reduce surgical risk and operation. In clinical cases, commercial valve stents are sometimes not available for children or special subjects due to restrictions in stent size. Hence, the handmade pulmonary valved conduit provides a strategy to design stents with customized size for valve replacement. In this paper, we propose a meta-learning-based intelligent model to train an estimator (including two sub-estimators) to determine optimal trileaflet parameters for customized trileaflet valve reconstruction. This estimation model overcomes the problem of empirical parameter determination. The meta-learning model possesses learning-to-optimization capability for training generalized regression neural network by particle swarm optimization algorithm. Through incremental training patterns, this scheme can gradually enhance optimization to provide refined parameters for customized designs that can be applicable to individuals of all age groups. The customized handmade pulmonary valved conduit was validated by assessing the regurgitation fraction and the heart pump efficiency using an experimental cardiopulmonary circulation loop system.

Hypervolemia screening in predialysis healthcare for hemodialysis patients using fuzzy color reason analysis

Maintaining adequate dry weight and fluid volume balance is an important issue for dialysis patients. Malnutrition and sodium intake are the primary factors that cause fluid volume imbalance and changes in body weights. Inadequate dry weight control results in higher levels of blood pressures and is related to various complications, such as volume overload, hypertension, congestive symptoms, and cardiovascular diseases. Moreover, inadequate fluid removal provokes hypotension during dialysis treatment. Thus, we propose an early warning tool based on fuzzy color reason analysis in predialysis healthcare for hypervolemia screening. The anthropometric method is a rapid, non-invasive, and simple technique for estimating the total body water. In this study, Watson standard formula is employed to estimate cross-sectional standard of total body water with the patient characteristics, including gender, age, height, and weight. In contrast to the experienced anthropometric formulas, Watson formula has less than 2% of margin errors and provides a criterion as a reference manner to estimate the total body water in patient’s normal dry weight. In addition, inadequate dry weight and total body water controls will lead to higher blood pressures. The systolic blood pressure is also an indicator to evaluate pre-hypertension of 120–139 mmHg and hypertension of greater than or equal to 140 mmHg. Therefore, the levels of two indicators, total body water and systolic blood pressure, are parameterized with fuzzy membership grades to describe the normal and the specific ranges of undervolemia and hypervolemia. A color reason analysis utilizes a hue–saturation–value color model to design a color perceptual manner for separating normal condition from hypervolemia or undervolemia. Normalized hue angle and saturation value provide a promising visual representation with color codes to realize the patients’ diagnosis. Dialysis patients with hypertension demonstrated that the proposed model can be used in clinical applications. In addition, a healthcare chair is carried out to measure blood pressure and weight in predialysis. The proposed assistant tool integrates an electronic pressure monitor and an electronic weight monitor, and fuzzy color reason analysis is also intended to be established in an intelligent vehicle via a WiFi wireless local area network for cloud computing.

Integrating Flexible Sensor and Virtual Self-Organizing DC Grid Model With Cloud Computing for Blood Leakage Detection During Hemodialysis

Blood leakage and blood loss are serious complications during hemodialysis. From the hemodialysis survey reports, these life-threatening events occur to attract nephrology nurses and patients themselves. When the venous needle and blood line are disconnected, it takes only a few minutes for an adult patient to lose over 40% of his / her blood, which is a sufficient amount of blood loss to cause the patient to die. Therefore, we propose integrating a flexible sensor and self-organizing algorithm to design a cloud computing-based warning device for blood leakage detection. The flexible sensor is fabricated via a screen-printing technique using metallic materials on a soft substrate in an array configuration. The self-organizing algorithm constructs a virtual direct current grid-based alarm unit in an embedded system. This warning device is employed to identify blood leakage levels via a wireless network and cloud computing. It has been validated experimentally, and the experimental results suggest specifications for its commercial designs. The proposed model can also be implemented in an embedded system.

Numerical evaluation and experimental validation of vascular access stenosis estimation.

Vascular access dysfunction commonly occurs in hemodialysis patients. Regularly monitoring and evaluating the vascular access condition is an important issue for these diseased patients. The objective of this study was to identify acoustic parameters and hemodynamics that related to changes in the stenosis of vascular access. In-vitro experimental circulation system offered pulsatile and physiological condition to simulate the arteriovenouse access in hemodialysis patient. We created the environments of various degrees of stenosis (DOS) inside the arteriovenouse access to simulate the stenotic conditions in patients. And we also used the computational fluid dynamics (CFD) to simulate the pressure distribution, primary axial velocity distribution, and secondary flow distribution in the same various DOS and boundary condition. There are two findings, one is recorded the bruit which caused by the fluctuation of fluid in different severe stenosis, the other is described the correlation between bruit and hemodynamic parameters. Experimental results show the time constants have linear regression with a positive correlation as the degree of stenosis (DOS) increases. Finally, in contrast to CFD computerized analysis and acoustic methods, the proposed parameter provides a feasibility index for evaluating the risk of AVG dysfunction in on-line/real time analysis.